Geometrical modeling of complete dental shapes by using panoramic X-ray, digital mouth data and anatomical templates

In the field of orthodontic planning, the creation of a complete digital dental model to simulate and predict treatments is of utmost importance. Nowadays, orthodontists use panoramic radiographs (PAN) and dental crown representations obtained by optical scanning. However, these data do not contain any 3D information regarding tooth root geometries. A reliable orthodontic treatment should instead take into account entire geometrical models of dental shapes in order to better predict tooth movements. This paper presents a methodology to create complete 3D patient dental anatomies by combining digital mouth models and panoramic radiographs. The modeling process is based on using crown surfaces, reconstructed by optical scanning, and root geometries, obtained by adapting anatomical CAD templates over patient specific information extracted from radiographic data. The radiographic process is virtually replicated on crown digital geometries through the Discrete Radon Transform (DRT). The resulting virtual PAN image is used to integrate the actual radiographic data and the digital mouth model. This procedure provides the root references on the 3D digital crown models, which guide a shape adjustment of the dental CAD templates. The entire geometrical models are finally created by merging dental crowns, captured by optical scanning, and root geometries, obtained from the CAD templates

Creation of 3D Multi-Body Orthodontic Models by Using Independent Imaging Sensors

In the field of dental health care, plaster models combined with 2D radiographs are widely used in clinical practice for orthodontic diagnoses. However, complex malocclusions can be better analyzed by exploiting 3D digital dental models, which allow virtual simulations and treatment planning processes. In this paper, dental data captured by independent imaging sensors are fused to create multi-body orthodontic models composed of teeth, oral soft tissues and alveolar bone structures. The methodology is based on integrating Cone-Beam Computed Tomography (CBCT) and surface structured light scanning. The optical scanner is used to reconstruct tooth crowns and soft tissues (visible surfaces) through the digitalization of both patients’ mouth impressions and plaster casts. These data are also used to guide the segmentation of internal dental tissues by processing CBCT data sets. The 3D individual dental tissues obtained by the optical scanner and the CBCT sensor are fused within multi-body orthodontic models without human supervisions to identify target anatomical structures. The final multi-body models represent valuable virtual platforms to clinical diagnostic and treatment planning

3D-reconstruction of human jaw from a single image : integration between statistical shape from shading and shape from shading.

Object modeling is a fundamental problem in engineering, involving talents from computer-aided design, computational geometry, computer vision and advanced manufacturing. The process of object modeling takes three stages: sensing, representation, and analysis. Various sensors may be used to capture information about objects; optical cam- eras and laser scanners are common with rigid objects, while X-ray, CT and MRI are common with biological organs. These sensors may provide a direct or indirect inference about the object, requiring a geometric representation in the computer that is suitable for subsequent usage. Geometric representations that are compact, i.e., capture the main features of the objects with minimal number of data points or vertices, fall into the domain of computational geometry. Once a compact object representation is in the computer, various analysis steps can be conducted, including recognition, coding, transmission, etc. The subject matter of this thesis is object reconstruction from a sequence of optical images. An approach to estimate the depth of the visible portion of the human teeth from intraoral cameras has been developed, extending the classical shape from shading (SFS) solution to non-Lambertian surfaces with known object illumination characteristics. To augment the visible portion, and in order to have the entire jaw reconstructed without the use of CT or MRI or even X-rays, additional information will be added to database of human jaws. This database has been constructed from an adult population with variations in teeth size, degradation and alignments. The database contains both shape and albedo information for the population. Using this database, a novel statistical shape from shading (SSFS) approach has been created. To obtain accurate result from shape from shading and statistical shape from shading, final step will be integrated two approaches (SFS,SSFS) by using Iterative Closest Point algorithm (ICP). Keywords: computer vision, shading, 3D shape reconstruction, shape from shading, statistical, shape from shading, Iterative Closest Point

Three-dimensional modeling of the human jaw/teeth using optics and statistics.

Object modeling is a fundamental problem in engineering, involving talents from computer-aided design, computational geometry, computer vision and advanced manufacturing. The process of object modeling takes three stages: sensing, representation, and analysis. Various sensors may be used to capture information about objects; optical cameras and laser scanners are common with rigid objects, while X-ray, CT and MRI are common with biological organs. These sensors may provide a direct or an indirect inference about the object, requiring a geometric representation in the computer that is suitable for subsequent usage. Geometric representations that are compact, i.e., capture the main features of the objects with a minimal number of data points or vertices, fall into the domain of computational geometry. Once a compact object representation is in the computer, various analysis steps can be conducted, including recognition, coding, transmission, etc. The subject matter of this dissertation is object reconstruction from a sequence of optical images using shape from shading (SFS) and SFS with shape priors. The application domain is dentistry. Most of the SFS approaches focus on the computational part of the SFS problem, i.e. the numerical solution. As a result, the imaging model in most conventional SFS algorithms has been simplified under three simple, but restrictive assumptions: (1) the camera performs an orthographic projection of the scene, (2) the surface has a Lambertian reflectance and (3) the light source is a single point source at infinity. Unfortunately, such assumptions are no longer held in the case of reconstruction of real objects as intra-oral imaging environment for human teeth. In this work, we introduce a more realistic formulation of the SFS problem by considering the image formation components: the camera, the light source, and the surface reflectance. This dissertation proposes a non-Lambertian SFS algorithm under perspective projection which benefits from camera calibration parameters. The attenuation of illumination is taken account due to near-field imaging. The surface reflectance is modeled using the Oren-Nayar-Wolff model which accounts for the retro-reflection case. In this context, a new variational formulation is proposed that relates an evolving surface model with image information, taking into consideration that the image is taken by a perspective camera with known parameters. A new energy functional is formulated to incorporate brightness, smoothness and integrability constraints. In addition, to further improve the accuracy and practicality of the results, 3D shape priors are incorporated in the proposed SFS formulation. This strategy is motivated by the fact that humans rely on strong prior information about the 3D world around us in order to perceive 3D shape information. Such information is statistically extracted from training 3D models of the human teeth. The proposed SFS algorithms have been used in two different frameworks in this dissertation: a) holistic, which stitches a sequence of images in order to cover the entire jaw, and then apply the SFS, and b) piece-wise, which focuses on a specific tooth or a segment of the human jaw, and applies SFS using physical teeth illumination characteristics. To augment the visible portion, and in order to have the entire jaw reconstructed without the use of CT or MRI or even X-rays, prior information were added which gathered from a database of human jaws. This database has been constructed from an adult population with variations in teeth size, degradation and alignments. The database contains both shape and albedo information for the population. Using this database, a novel statistical shape from shading (SSFS) approach has been created. Extending the work on human teeth analysis, Finite Element Analysis (FEA) is adapted for analyzing and calculating stresses and strains of dental structures. Previous Finite Element (FE) studies used approximate 2D models. In this dissertation, an accurate three-dimensional CAD model is proposed. 3D stress and displacements of different teeth type are successfully carried out. A newly developed open-source finite element solver, Finite Elements for Biomechanics (FEBio), has been used. The limitations of the experimental and analytical approaches used for stress and displacement analysis are overcome by using FEA tool benefits such as dealing with complex geometry and complex loading conditions

Double osseous flaps for simultaneous midfacial and mandible reconstruction: Automation in surgical complexity within an entirely computerized workflow

Introduction: Broad maxillofacial surgical resections involving both the midface and the mandible represent a challenge in terms of reconstruction. Although several papers have explored the possibility of simultaneously using two microsurgical flaps, reports on the implementation of a dual osseous flap strategy are limited, and mainly addressed to static anatomical reconstruction, regardless of functional implications. In particular, there is a lack in the literature of a unifying protocol which illustrates how technology including virtual planning, statistical shape modeling, virtual occlusion, 3D-printing and patient-specific implants can address the functional and accuracy needs required for an optimal reconstruction. Materials and methods: In this paper, the Authors present their preliminary experience in a two-center study, showing how broad maxillofacial defects, requiring a simultaneous reconstruction in both the mandible and the midface, can be successfully reconstructed using the combination of two osseous flaps in an automated sequence in which all steps are anticipately defined in a virtual plan, accounting for the optimal alignment of temporomandibular joint, predicting the final occlusion and defining a mandibular shape according to a statistical shape model. Results: Average RMSE for the iliac bone crest flap was of 3.2 ± 0.36 mm; for the fibula flap, RMSE value was of 2.3 ± 0.65 mm, for patient-specific implants, for mandibular prostheses the average RMSE was 2.46 mm with 0.76 mm standard deviation. Temporomandibular joint function increased when a TMJ prosthesis was placed. Conclusions: Double bone free flap is a valuable resource to reconstruct wide defects that simultaneously involve two thirds of the cranio-maxillo-facial skeleton, but a careful virtual planning study should be always performed before approaching this surgical option

Prediction of Root Form Using Crown Data: Mandibular Left First Premolar

Introduction: The purpose of this study was to determine if a statistical shape model (SSM) of the lower left first premolar, consisting of both crown and root data, could adequately describe the root form from a surface scan consisting of only crown data. Secondly, it tested if there were any angles or measurements on the tooth crown that correlate with any aspects of root morphology. The average orthodontist practicing today or in the near future is likely to use or own a digital intraoral scanner in their office. Yet optical scans only allow visualization of the crowns of teeth and external structures. We know that the orthodontic profession and the published literature support treatment of the teeth crowns and their roots in all three planes of space.1-7 Data acquired through CBCT imaging provides an accurate representation of the teeth and their roots, but it comes at a cost of relatively high radiation exposure.22-38 For this reason, the use of CBCT and other radiographic modalities to analyze orthodontic treatment is generally limited to the least use necessary.8 This study set out to find if statistical shape modeling could provide the practitioner with root form and/or positional data that could aid in patient care. Materials and Methods: Surface scans of 76 extracted mandibular first premolar teeth were entered into statistical software that created a statistical shape model from the population data and select landmark points. Then, using only the optical surface scans of 16 real patient crowns, the statistical model predicted a root form. Real patient roots, after being segmented from CBCT’s, were compared to the predicted roots and agreement was measured. Statistical analysis was performed using intraclass correlation tests and Euclidean Distance Matrix Analysis (EDMA), a technique used to compare biologic shapes using landmark points, to compare the 3D root shapes and dimensions. Spearman’s rho test was used to determine relationships within the 76 teeth population crown and root measurements. Results: The comparison between averaged real and predicted root forms using EDMA showed no significant differences. However, when an intraclass correlation coefficient test compared linear and angular measurements between individual real and predicted teeth forms, the agreement was weak or non-existent. For the population of 76 extracted mandibular first premolars, there were several different measurements and angles that showed moderate or weak agreement to each other. None of the tested measurements within the population showed strong, predictive correlation between crown and root measurements. Conclusions: For the mandibular first premolar, we were able to accurately predict root form from only optical crown scans when we averaged the real and predicted comparisons. On an individual level, the real and predicted teeth forms were statistically different. There were several moderate and weak agreements between measurements in the population of 76 extracted mandibular first premolars

Detecting missing teeth on PMCT using statistical shape modeling

The identification of teeth in 3D medical images can be a first step for victim identification from scant remains, for comparison of ante- and postmortem images or for other forensic investigations. We evaluate the performance of a tooth detection approach on mandibles with missing parts or pathologies based on statistical shape models. The proposed approach relies on a shape model that has been built from the full lower jaw, including the mandible and teeth. The model is fitted to the target, resulting in a reconstruction, in addition to a label map that indicates the presence or absence of teeth. We evaluate the accuracy of the proposed solution on a dataset consisting of 76 target mandibles, all extracted from CT images and exhibiting various cases of missing teeth or other cases, such as roots, implants, first dentition, and gap closure. We show an accuracy of approximately 90% on the front teeth (including incisors and canines in our study) that decreases for the molars due to high false-positive rates at the wisdom teeth level. Despite the drop in performance, the proposed approach can be used to obtain an estimate of the tooth count without wisdom teeth, tooth identification, reconstruction of the existing teeth to automate measurements taken as part of routine forensic procedures, or prediction of the missing teeth shape. In comparison to other approaches, our solution relies solely on shape information. This means it can be applied to cases obtained from either medical images or 3D scans because it does not depend on the imaging modality intensities. Another novelty is that the proposed solution avoids heuristics for the separation of teeth or for fitting individual tooth models. The solution is therefore not target-specific and can be directly applied to detect missing parts in other target organs using a shape model of the new target

Dental Diagnosis and Treatment Assessments: Between X-rays Radiography and Optical Coherence Tomography

A correct diagnosis in dental medicine is typically provided only after clinical and radiological evaluations. They are also required for treatment assessments. The aim of this study is to establish the boundaries from which a modern, although established, imaging technique, Optical Coherence Tomography (OCT), is more suitable than the common X-ray radiography to assess dental issues and treatments. The most common methods for daily-basis clinical imaging are utilized in this study for extracted teeth (but also for other dental samples and materials), i.e., panoramic, intraoral radiography, and three-dimensional (3D) cone beam computed tomography (CBCT). The advantages of using OCT as an imaging method in dentistry are discussed, with a focus on its superior image resolution. Drawbacks related to its limited penetration depth and Field-of-View (FOV) are pointed out. High-quality radiological investigations are performed, measurements are done, and data collected. The same teeth and samples are also imaged (mostly) with an in-house developed Swept Source (SS)-OCT system, Master-Slave enhanced. Some of the OCT investigations employed two other in-house developed OCT systems, Spectral Domain (SD) and Time Domain (TD). Dedicated toolbars from Romexis software (Planmeca, Helsinki, Finland) are used to perform measurements using both radiography and OCT. Clinical conclusions are drawn from the investigations. Upsides and downsides of the two medical imaging techniques are concluded for each type of considered diagnosis. For treatment assessments, it is concluded that OCT is more appropriate than radiography in all applications, except bone-related investigations and periodontitis that demand data from higher-penetration depths than possible with the current level of OCT technology. View Full-Tex